Enhanced uniqueness for pattern recognition

ABSTRACT

The present invention describes a test structure with a first set of features which is a subset of product features; and a second set of features adjacent to the first set of features, the second set occupying a smaller area than the first set and the second set being similar to the first set yet being distinguishable from surrounding structures.

BACKGROUND OF THE INVENTION

[0001] 1. Field of the Invention

[0002] The present invention relates to the field of semiconductorintegrated circuit (IC) manufacturing, and more specifically, to amethod of improving pattern recognition for critical dimension (CD)measurement in an optical microscope or a Scanning Electron Microscope(SEM).

[0003] 2. Discussion of Related Art

[0004] During fabrication of an integrated circuit (IC), many parametersof the semiconductor devices must be monitored to maximize yield. Inparticular, it is desirable to measure critical dimension (CD) ofcertain features, especially on the critical layers such as shallowtrench isolation, polysilicon gate, contact, and first metal.

[0005] The CD for a layer may be monitored in-line by sampling theproduct features on various die across a wafer. However, it is oftenadvantageous to measure test structures that may be placed in thescribelines separating the die. CD measurements are usually performedafter develop since rework is still possible at that point by strippingthe photoresist. CD measurements are also done after etch to determinethe etch bias.

[0006] CD measurements are often taken optically on a tool withconventional microscope optics or with laser-spot scanning. Theresolution of an optical probe can be increased by about 30% if aconfocal configuration is used. However, it is usually necessary to usea scanning electron microscope (SEM) to measure a CD smaller than about200 nanometers. To avoid charging of the sample, the accelerationvoltage should be kept below about 600 to 1000 volts or the vacuumshould be kept low. Field emission guns are often used to produce goodimages.

[0007] A SEM may be used to measure the CD of a structure after developor after etch. After loading a wafer into the SEM, a motorized stagemoves the wafer to a specified location based on an external coordinatesystem. Then, pattern recognition of the captured image is performed tolocate the desired structure in the vicinity. Finally, the CD of thestructure is measured.

[0008] Although sophisticated algorithms are available for patternrecognition, various parameters in the recipe must still be empiricallyoptimized to improve the robustness of the recipe. If the acceptancelevel is too relaxed, pattern recognition may mistakenly identify anincorrect feature. Then the corresponding CD measurement would not bemeaningful, thus, degrading data integrity and compromising in-lineprocess control. On the other hand, if the acceptance level is toostringent, the pattern recognition may fail, thus, mandating manualintervention by the user. At a minimum, the processing of the wafer isinterrupted. Of even more concern is that the feedback from the SEM tothe process tools is delayed, needlessly leading to production of morewafers that are out of specification and have to be scrapped.

[0009] Thus, what is needed is a structure for and a method of improvingpattern recognition.

BRIEF DESCRIPTION OF THE DRAWINGS

[0010]FIG. 1(a) is an illustration of a plane view of chips separated byscribelines on a wafer.

[0011]FIG. 1(b) is an illustration of a plane view of 4 adjacent chips,each chip having a metrology cell located in each corner.

[0012]FIG. 1(c) is an illustration of a plane view of a cluster of 4identical metrology cells at an intersection of a horizontal scribelineand a vertical scribeline.

[0013]FIG. 1(d) is an illustration of a plane view of a test structurehaving a single array.

[0014]FIG. 2 is an illustration of a plane view of a test structurehaving multiple arrays.

[0015]FIG. 3 is an illustration of a plane view of a test structurehaving a first set of features and a second set of features.

[0016] FIGS. 4(a)-(c) are illustrations of modifications ortransformations to provide sufficient uniqueness to a set of features.

[0017]FIG. 5 is a flowchart of a typical geometric transformation.

DETAILED DESCRIPTION OF THE PRESENT INVENTION

[0018] In the following description, numerous details, such as specificmaterials, dimensions, and processes, are set forth in order to providea thorough understanding of the present invention. However, one skilledin the art will realize that the invention may be practiced withoutthese particular details. In other instances, well-known semiconductorequipment and processes have not been described in particular detail soas to avoid obscuring the present invention.

[0019] The present invention describes a structure for and a method ofimproving pattern recognition for a tool, such as an optical microscopeor a scanning electron microscope (SEM). The structure includes a firstset of features sufficiently resembling certain product features toallow monitoring of important parameters, such as a critical dimension(CD) of a feature or a thickness of a film layer, for compliance withspecification. The structure further includes a second set of featuressufficiently unique compared with nearby structures to allowdistinguishing them. The method includes a procedure to design such astructure and a procedure to perform pattern recognition on such astructure.

[0020] In a SEM, an electron beam is raster scanned on a sample, such asa wafer or a photomask, and the secondary electron signal is detectedwith a detector, such as a scintillator and a photomultiplier, or amulti-channel plate. The sample is usually scanned multiple times toproduce an image of the field of view (FOV) to be stored in a buffer.Digital image processing is performed on the acquired image to identifythe correct structure in the field of view.

[0021] An integrated circuit (IC) is typically fabricated as a chip on asemiconductor wafer 100, as shown in FIG. 1(a). One or more chips arearranged within a die 102 that is replicated by photolithography in aregular pattern many times across the wafer 100. The die 102 areseparated by horizontal scribelines 105 and vertical scribelines 107along which they are subsequently scribed and diced to be packaged.

[0022] However, wafers often become distorted by thermal cycling duringfabrication. Layer-to-layer overlay errors may also accumulate.Consequently, a desired structure may not be found initially when astage holding a wafer sample in a SEM has been moved to a specifiedlocation. Then, it becomes necessary to search other candidatestructures in the surrounding area to find the desired structure.

[0023] Pattern recognition is used to compare a candidate structure witha reference structure stored in memory. A score is calculated based onnormalized correlation. All candidate structures having scores exceedinga preset threshold value are ranked. The candidate structure having thehighest score is identified as the desired structure. However, anincorrect structure may still be selected, especially if the sample isnot loaded properly on the stage or the stage is not calibratedprecisely.

[0024] At a particular layer of processing a wafer, it may be desired tomeasure a feature 117 in a test structure 110 that is representative ofthe product in the chip, as shown in FIG. 1(c). Feature 117 is shown asa hole that is approximately circular. In other cases, the feature 117may have a different geometry, such as a polygon, a line, or a space.The feature 117 may have symmetry along 2 axes, 1 axis, or none at all.

[0025] A test structure 110 is usually placed near each corner of a die102 in the scribeline, as shown in FIG. 1(b). As a result, four copiesof the test structure will be located near each other in a cluster atthe intersection of a horizontal scribeline 105 and a verticalscribeline 107. FIG. 1(c) shows test structures 110, 120, 130, and 140that are located in a cluster 150.

[0026] However, instead of measuring test structure 110, a SEM maymistakenly select test structure 120 or 130 or 140, all of which can befound in the vicinity in the same cluster 150. As a result, instead ofmeasuring the center feature 117, the SEM may measure the center feature127 or 137 or 147. Thus, the SEM has found the wrong test structure inthe cluster 150 at the intersection of 4 chips.

[0027] The CD 112 of a feature 115, as shown in FIG. 1(d), may vary,depending on the number of nearby features, their proximity, theirshapes, and their CDs. A proximity effect will result from a variationin light intensity caused by a local difference in pattern density. Inorder to accommodate the proximity effect, it is desirable to surroundthe feature to be measured with a sufficient number of identicalfeatures. For example, a test structure 110 being monitored at a contactlayer may have holes arranged in a 5-by-5 array 110 a with a pitch 114in the horizontal direction and a pitch 115 in the vertical direction.The pitch is defined as the center-to-center spacing of adjacentfeatures in an array of repeating, identical features. Then CD 112 wouldbe measured on the center feature 117 of the array.

[0028] Even if the correct test structure 110 in the cluster 150 were tobe selected, the SEM may mistakenly measure the wrong feature. Forexample, instead of measuring the center feature 117 in the correct teststructure 110, the SEM may select feature 119 that is nearby. See FIG.1(c). Thus, the SEM has found the wrong feature 119 within the correcttest structure 110 in the cluster 150.

[0029] A test structure 110 may include only one array 110 a, as shownin FIG. 1 (d). However, a test structure 210 may also include multiplearrays 210 a, 210 b, 210 c, 210 d, as shown in FIG. 2. In the lattercase, each array in the test structure 210 may be designated for use ona separate layer during the processing of the wafer.

[0030] Alternatively, the multiple arrays in the test structure 210 canbe used on the same layer. Then process latitude may be characterized bystudying the effect on CD of focus and exposure dose across a field andacross a wafer. For example, a first array 210 a may have holes with thesame CD and the same pitch as the product. A second array 210 b may haveholes with smaller CD and the same pitch as the product. A third array210 c may have holes with larger CD and the same pitch as the product. Afourth array 210 d may have the reverse polarity, in other words,islands instead of holes, with the same CD and the same pitch as theproduct.

[0031] For a test structure 210 that includes several similar arrays, asshown in FIG. 2, the SEM may mistakenly measure center feature 217 b or217 c or 217 d instead of the correct 217 a. Thus, the SEM has found thewrong array within the correct test structure 210.

[0032] The present invention adds sufficient uniqueness to the desiredtest structure 250 so that pattern recognition can result in anunambiguous and correct identification despite the proximity of othersimilar structures in the vicinity. Pattern recognition includesevaluation of contrast, density, tone, and grey scale in an image.

[0033] The test structure 250 includes a first set 245 of features and asecond set 255 of features. The first set 245 of features is a subset ofthe product features to be monitored. The second set 255 of features issimilar to the first set 245 of features, but differs in one or moreways. The second set 255 of features may be merged directly into thefirst set 245 of features or may be separated by a buffer 1 5 region265. Pattern recognition may be performed on part or all of the firstset 245 of features and part or all of the second set 255 of features.Alternatively, pattern recognition may be done only on part or all ofthe second set 255 of features.

[0034] Uniqueness is provided to the test structure 250 by the secondset 255 of features. The uniqueness may involve one or morecharacteristics such as size, linewidth, space, pitch, orientation,pattern factor, polarity, number of edges, and number of features.

[0035] Size refers to the dimensions of a set of features, such as thelength and the width of an array of holes. Linewidth refers to theshortest linear distance between the facing edges of a feature, such asthe diameter of a hole or the width of a line. Space refers to theshortest linear distance between the facing edges of adjacent features.Pitch refers to the sum of a linewidth and an adjacent space in aregularly repeating pattern of identical features. Orientation refers tothe angular placement of a feature in the die.

[0036] Pattern factor refers to the percentage of total area (featuresand spaces) that is occupied by the interior of the features. Polarityrefers to placement of the interior of a feature on one side of an edgeversus the other side of the edge. Polarity is reversed by exchangingthe interior of a feature with the exterior of a feature. Polarityaffects the perceived grey scale in an image.

[0037] Number of edges refers to number of intersections where twopredominantly distinct surfaces meet. An edge defines a boundary,usually quite abrupt, between the interior of a feature and the exteriorof a feature.

[0038] The second set 255 of features in the present invention should beas small and unobtrusive as possible in order to avoid taking up toomuch space. In general, the second set 255 of features occupies asmaller area than the first set 245 of features. Furthermore, the secondset 255 of features should not be vastly different in shape anddimension from the first set 245 of features so as to avoid violatinggroundrules for design and layout of the product.

[0039] The second set 255 of features is created by modifying a template253. The template 253 is based on the first set 245 of features. Themodification usually involves geometric transformation of the features.For example, if the template 253 includes product features such as holesarranged in a square array, the second set 255 of features may includeadditional holes 254 so the array becomes face-centered. See FIG. 4(a).

[0040] If the template 253 includes parallel lines, the second set 255of features may have jogs 257 in the lines. See FIG. 4(b).

[0041] If the template 253 has features that are predominantlyrectilinear in the x-and y-directions, the modification can introduce arotation 259 to form the second set 255 of features. See FIG. 4(c).

[0042] Another embodiment of the present invention involves a method ofdesigning a test structure with sufficient uniqueness to facilitatesuccessful pattern recognition of its image. The test structure has afirst set of features and a second set of features. The second set offeatures serves to provide sufficient uniqueness to facilitate patternrecognition of the test structure. In general, similar test structuresthat are located near each other may be distinguished by modifying theirsecond set of features.

[0043] A flowchart of a typical geometric transformation according tothe present invention is shown in FIG. 5. Depending on the situation,the individual operations described below may be performed in adifferent sequence. As needed, some operations may also be performediteratively. If desired, the claimed invention may be automated, inwhole or in part, using software and a computer.

[0044] First, as shown in block 10, a subset is extracted from theproduct features to form a first set of features.

[0045] Second, as shown in block 20, a portion is extracted from thefirst set of features to form a template. A portion may represent 3 to15 percent of the first set of features.

[0046] Third, the template is transformed into a second set of featuresby three operations: rotating, space scaling, and linewidth scaling.

[0047] As shown in block 33, the template is rotated in either acounterclockwise or a clockwise direction. The rotation is typically inthe range of 15 to 55 degrees, but may be as small as 0 or as large as90 degrees. A negative rotation is counterclockwise while a positiverotation is clockwise.

[0048] As shown in block 36, the spaces between the features in thetemplate are changed by a space scaling factor. The space scaling factoris typically in the range of −0.85 to +2.00. A negative space scalingfactor reduces a space while a positive space scaling factor increases aspace.

[0049] As shown in block 39, the linewidths of the features in thetemplate are changed by a linewidth scaling factor. The linewidthscaling factor is typically in the range +0.25 to −0.25. A positivelinewidth scaling factor enlarges a feature while a negative linewidthscaling factor shrinks a feature. The linewidth scaling factor and thespace scaling factor usually have opposite algebraic signs.

[0050] Fourth, as shown in block 40, a buffer zone is added. A bufferzone essentially represents a lateral displacement. The buffer zone maysimplify design and layout since different first sets and differentsecond sets may be combined as desired.

[0051] Fifth, as shown in block 45, the first set of features and thesecond set of features are merged to form a test struicture.

[0052] Accuracy of pattern recognition may be reduced if the patternfactor is too low. Sensitivity of pattern recognition is also affectedby local variation in pattern factor across a test structure. Theaverage change in pattern factor of the test structure after scalingboth the space and the linewidth should be kept in the range 0.15 to+0.15. This can be achieved because the area occupied by the first set245 of features is usually much larger than the area occupied by thesecond set 255 of features. It is desirable not to change pattern factortoo drastically in the test structure because the fabrication process isnormally optimized for a particular pattern factor in the product.

[0053] A further embodiment of the present invention involves a methodof performing pattern recognition of a test structure that has beendesigned with sufficient uniqueness as described above. The method is tostore an image of a reference structure with the appropriate uniqueness,load a sample on a stage, move the stage to go to a nominal location onthe sample based on an external reference coordinate system, adjust thestage to the appropriate orientation, adjust the optical column to theappropriate magnification, focus and fine-tune an image of a teststructure, capture the test image in a field of view, store the testimage in a buffer, scan all portions of a specified region of interest(ROI) of the test image, recall the reference image, perform anormalized correlation of each portion relative to the reference image,compute a score for the degree of similarity of each portion to thereference image, discard the portions with scores below the allowablethreshold, rank the portions from highest score to lowest score,determine the location of the portion with the highest score, comparewith the nominal location, calculate offsets and scaling factors, movethe stage to a measurement location within the field of view, changemagnification, focus and fine-tune an image of a measurement structure,capture the measurement image in the field of view, store themeasurement image in a buffer, acquire a signal profile of themeasurement image, and use an edge detection algorithm to measure CD.The CD may be determined using algorithms employing techniques such aslinear regression (of the base line and the slope line), peak-to-peak,and threshold.

[0054] In general, the score depends on the degree of match between thereference image and the test image. In other words, the score depends onthe first set of features and the second set of features which form thetest structure. Normalized correlation is used to determine the scorebecause it is not susceptible to linear changes in brightness of thecaptured image. However, normalized correlation can be affected bynonlinear changes, such as charging of a sample.

[0055] Many embodiments and numerous details have been set forth abovein order to provide a thorough understanding of the present invention.One skilled in the art will appreciate that many of the features in oneembodiment are equally applicable to other embodiments. One skilled inthe art will also appreciate the ability to make various equivalentsubstitutions for those specific materials, processes, dimensions,concentrations, etc. described herein. It is to be understood that thedetailed description of the present invention should be taken asillustrative and not limiting, wherein the scope of the presentinvention should be determined by the claims that follow.

We claim:
 1. A structure comprising: a first set of features disposed inthe scribeline, said first set of features being a subset of productfeatures; and a second set of features disposed adjacent to said firstset of features, said second set occupying a smaller area than saidfirst set, said second set being similar to said first set, said secondset being distinguishable from surrounding structures.
 2. The structureof claim 1 wherein critical dimension (CD) is measured on said first setof features.
 3. The structure of claim 1 wherein said first set offeatures and said second set of features differ in spaces betweenfeatures.
 4. The structure of claim 1 wherein said first set of featuresand said second set of features differ in linewidths of features.
 5. Thestructure of claim 1 wherein said first set of features and said secondset of features have the same pitch for features.
 6. The structure ofclaim 1 wherein said first set of features comprises a first array ofholes.
 7. The structure of claim 6 wherein said first array of holescomprises a 5-by-5 square array of holes.
 8. The structure of claim 6wherein said second set of features comprises a second array of holes.9. The structure of claim 8 wherein said second array of holes differsfrom said first array of holes in size of array.
 10. The structure ofclaim 8 wherein said second array of holes differs from said first arrayof holes in space between holes.
 11. The structure of claim 8 whereinsaid second array of holes differs from said first array of holes inlinewidths of holes.
 12. A method comprising: extracting a subset fromproduct features to form a first set of features; extracting a smallportion from said first set of features to form a template; transformingsaid template into a second set of features by rotating said template;scaling spaces between features in said template; scaling linewidths offeatures in said template; merging said first set and said second set offeatures to form a test structure.
 13. The method of claim 12 whereincritical dimension (CD) is measured on said first set of features.
 14. Amethod comprising: storing a reference image of a test structure, saidreference image comprising a first set of features and a second set offeatures, said first set of features being a subset of product features,said second set of features disposed adjacent to said first set offeatures, said second set occupying a smaller area than said first set,said second set being similar to said first set, said second set beingdistinguishable from surrounding structures; capturing a test image of asample, said test image having a plurality of portions; performingpattern recognition of each of said portions relative to said referenceimage; evaluating similarity of each of said portions to said referenceimage; determining a score for each of said portions; ranking saidportions from highest score to lowest score; and determining location onsaid sample of said portion with highest score.
 15. The method of claim14 wherein said score depends on said first set of features and saidsecond set of features.
 16. The method of claim 14 wherein said firstset of features comprises a first array of holes and said second set offeatures comprises a second array of holes, said second array of holesdiffering from said first array of holes.